Patient Outcomes and Unit Composition With Transition to a High-Intensity ICU Staffing Model: A Before-and-After Study.

Unlabelled: Provider staffing models for ICUs are generally based on pragmatic necessities and historical norms at individual institutions. A better understanding of the role that provider staffing models play in determining patient outcomes and optimizing use of ICU resources is needed.

Objectives: To explore the impact of transitioning from a low- to high-intensity intensivist staffing model on patient outcomes and unit composition.

Design Setting And Participants: This was a prospective observational before-and-after study of adult ICU patients admitted to a single community hospital ICU before (October 2016-May 2017) and after (June 2017-November 2017) the transition to a high-intensity ICU staffing model.

Main Outcomes And Measures: The primary outcome was 30-day all-cause mortality. Secondary outcomes included in-hospital mortality, ICU length of stay (LOS), and unit composition characteristics including type (e.g., medical, surgical) and purpose (ICU-specific intervention vs close monitoring only) of admission.

Results: For the primary outcome, 1,219 subjects were included (779 low-intensity, 440 high-intensity). In multivariable analysis, the transition to a high-intensity staffing model was not associated with a decrease in 30-day (odds ratio [OR], 0.90; 95% CI, 0.61-1.34; = 0.62) or in-hospital (OR, 0.89; 95% CI, 0.57-1.38; = 0.60) mortality, nor ICU LOS. However, the proportion of patients admitted to the ICU without an ICU-specific need did decrease under the high-intensity staffing model (27.2% low-intensity to 17.5% high-intensity; < 0.001).

Conclusions And Relevance: Multivariable analysis showed no association between transition to a high-intensity ICU staffing model and mortality or LOS outcomes; however, the proportion of patients admitted without an ICU-specific need decreased under the high-intensity model. Further research is needed to determine whether a high-intensity staffing model may lead to more efficient ICU bed usage.